Companies · AI / ML

winfuncSummer 2024Active

San Francisco · CA, USA · AI / ML · founded 2024 · https://winfunc.com

Diligence memoA one-page analyst read on winfunc — recommendation, valuation, rhythm, risks.
Total raised · real
0
Rounds
Latest step-up
Top 39%
Sector rank · raised
Latest stage · inferred

winfunc: limited disclosed financing to assess.

Synthesized from the figures below est. — every claim rests on a number shown on this page.

Where it sits in AI / ML

winfunc is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2024. By capital raised it ranks mid-pack (ahead of 62% of sector peers), and mid-pack by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst

ai-native security engineering for mission critical codebases

Winfunc (winfunc.com) is an AI Hacker that autonomously finds, verifies, and patches security vulnerabilities in codebases, just like a human security engineer would. Winfunc can find business logic errors with context-aware scanning and automate the full auditing cycle to generate reports with zero false positives. Winfunc's agent has found vulnerabilities in Google, Supabase, Sentry, Cal, Gumroad, Bun, Hoppscotch, etc.

AIArtificial IntelligenceB2BSaaSSecurityai/ml
Find winfunc online

As reported in public records reported — not modeled.

US
Jurisdiction
Amount raised vs valuation, by round

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

Financing ladder & sequence gaps

No staged rounds to sequence.

Modeled valuation trajectory
Base estimate est.
Conservative case
Upside case
Modeled post-money

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Financing rhythm
Avg between rounds
Capital velocity
On record since
First round
0
Rounds on file
How it compares to the market

Benchmarked against 2067 companies in AI / ML. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Total raised — vs sector median (real $, all stages)
This company
Sector median$4.7M
Modeled value — vs sector median (estimate, all stages)
This company
Sector median$27.9M

Raised more than 62% of sector peers (real $). Modeled value above 62% of peers (estimate).

Full financing history

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

StageAmount · realAnnouncedPost-money · estValue · estConf.
No rounds recorded.
Intelligence
Modeled next raise
Modeled next size est.
Last step-up
Capital velocity

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

Registry & provenance

winfunc is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

United States
Country of record
US
Jurisdiction
Similar companies

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

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Semantically similar

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

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CommodityAI
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Frequently asked
What does winfunc do and where is it based?
winfunc operates in the AI / ML sector, based in San Francisco, CA, USA. ai-native security engineering for mission critical codebases
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